Title page for etd-0905111-152723


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URN etd-0905111-152723
Author Wei-Shing Wu
Author's Email Address No Public.
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Department Marine Environment and Engineering
Year 2010
Semester 2
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Maritime Engineering Risk Assessment by Integrating Interpretive Structural Modeling and Bayesian Network, a Case Study of Offshore Piping
Date of Defense 2011-07-25
Page Count 84
Keyword
  • Bayesian network (BN)
  • Offshore piping
  • Interpretive Structural Modeling (ISM)
  • Maritime engineering
  • Risk assessment
  • Abstract Taiwan, as an island country, should place future aspiration on the usages of ocean energy and marine resources, such as offshore wind power and deep ocean water. The sound development of marine services relies on a strong industry of maritime engineering. The perilous marine environment has posed the highest risk for all maritime civil engineering activities. It is therefore imperative to restrain the risk associated with current maritime work, other than just engineering technique itself. By doing so, the quality of maritime work can be assured, and as the improvement of overall engineering capability, Taiwan can compete worldwide in the maritime engineering industry.
    Maritime works have developed their own standard construction procedures. To mitigate risk of maritime works depend mainly on the domain experts’ experience and know-how. However, problems appear when less experienced experts are available, or qualitative experience exists in a narrative form. It is therefore important to structure clearly an engineering risk factor relation, and quantify and control these risk factors. The proposed study will first collect and review related literatures, and then interview an expert from the designate maritime service company to establish the risk factors associated with offshore piping. Eventually a complete Bayesian network (BN) was formulated based on the cause-effect diagram, using Interpretive Structural Modeling (ISM), and experts’ experience was transformed into a set of prior and conditional probability to be embedded in the BN. The BN can clearly show that certain earlier operational factors affect final operational process deeply. Besides, the backward reasoning using the BN is possible to identify the factors causing a project failure.
    Advisory Committee
  • Machine Hsie - chair
  • Meng-tsung Lee - co-chair
  • Shu-Kuang Ning - co-chair
  • Yang-Chi Chang - advisor
  • Files
  • etd-0905111-152723.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2011-09-05

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